Bibliometric analysis of research on the application of deep learning to ophthalmology
The analysis of fundus images and the clinical application of deep learning techniques have emerged as prominent research areas in the field of ophthalmology. The substantial increase in publications and citations signifies the expanding impact and global collaboration in the application of deep learning research to ophthalmology. By identifying four distinct clusters representing sub-topics in deep learning ophthalmology research, this study contributes to the understanding of current trends and potential future advancements in the field.
Authors
- Min Zhao (ORCID: https://orcid.org/0000-0001-9577-425X)
- Jiangyue Zhao
- Zhongqing Wang (ORCID: https://orcid.org/0000-0002-3281-5322)
- Peng Cheng (ORCID: https://orcid.org/0000-0001-6379-554X)
- Haoxin Guo
- Junshi Dai
- Xusheng Cao (ORCID: https://orcid.org/0000-0002-4885-4537)
Institutions
- Fourth Affiliated Hospital of China Medical University (CN)
- First Hospital of China Medical University (CN)
- China Medical University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-31
- DOI
- https://doi.org/10.21037/qims-24-1340
- Citations
- 2
- Primary Topic
- Ophthalmology and Visual Health Research
- Type
- article
- Field-Weighted Citation Impact
- 1.08
Funders
- Shenyang Science and Technology Bureau